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Neural Networks and Genetic Algorithms as Forecasting Tools: A Case Study on German Regions


  • Roberto Patuelli
  • Peter Nijkamp
  • Simonetta Longhi

    (Institute for Social and Economic Research, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, England)

  • Aura Reggiani

    (Department of Economics, Faculty of Statistics, University of Bologna, Piazza Scaravilli 2, 40126 Bologna, Italy)


This paper develops and applies neural network (NN) models to forecast regional employment patterns in Germany. Computer-aided optimization tools that imitate natural biological evolution to find the solution that best fits the given case (namely, genetic algorithms, GAs) are also used to detect the best NN structure. GA techniques are compared with more ‘traditional’ techniques which require the supervision of experienced analysts. We test the performance of these techniques on a panel of 439 districts in West and East Germany. Since the West and East datasets have different time spans, the models are estimated separately for West and East Germany. The results show that the West and East NN models perform with different degrees of precision, mainly because of the different time spans of the two datasets. Automatic techniques for the choice of the NN architecture do not seem to outperform selection procedures based on the supervision of expert analysts.

Suggested Citation

  • Roberto Patuelli & Peter Nijkamp & Simonetta Longhi & Aura Reggiani, 2008. "Neural Networks and Genetic Algorithms as Forecasting Tools: A Case Study on German Regions," Environment and Planning B, , vol. 35(4), pages 701-722, August.
  • Handle: RePEc:sae:envirb:v:35:y:2008:i:4:p:701-722

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    Cited by:

    1. Robert Lehmann & Klaus Wohlrabe, 2014. "Regional economic forecasting: state-of-the-art methodology and future challenges," Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 218-231.

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    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs


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